The present invention relates, in general, to image processing, and more particularly, to detecting defects in objects using a novel image processing method.
In the past, a variety of image processing or pattern recognition techniques have been used to detect defects in objects such as semiconductor devices. These prior defect detection methods typically involve comparing an image of an object to be tested to an image of a defect-free object or other known reference pattern. One problem with these prior techniques is registration. The prior methods typically require exact registration between images of the object to be tested and the reference pattern. Often, a digitized image of an object to be tested has variations in feature widths and locations due to the digitizing algorithms, magnification differences, physical orientation of the objects, and variations in the physical size of the objects. Because of the variations, defect-free shapes can be interpreted as a defect.
An additional problem is the resolution that can be achieved. Because of the variations, the grey level images typically could not be used to accurately locate defects that were near the edges of defect-free features of the object. Consequently, objects may have defects that are not detected by these prior methods.
Accordingly, it is desirable to have a method of detecting defects that does not compare grey level images of different objects, that does not interpret grey level image variations as a defect, and that does not interpret variations as a defect.